Results 101 to 110 of about 4,342 (209)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingSparse unmixing, which introduces a large spectral library to transform the problem of mixed-pixel decomposition into the search for an optimal subset of endmembers that best represents the spectral characteristics of an image, has become a prominent ...
Fan Li +8 more
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Remote Sensing, 2019 The high interior heterogeneity of land surface covers in high-resolution image of coastal cities makes classification challenging. To meet this challenge, a Multi-Scale Superpixels-based Classification method using Optimized Spectral−Spatial ...
Aizhu Zhang +8 more
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Image Haze Removal Based on Superpixels and Markov Random Field
, 2020 Image haze removal is critical for autonomous driving. However, it is a challenging task for the existing image dehazing algorithms to eliminate the block effect completely and handle objects similar to light (such as snowy objects and white buildings ...
Yibo Tan, Guoyu Wang
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Superpixel Segmentation: An Evaluation
, 2015 In recent years, superpixel algorithms have become a standard tool in computer vision and many approaches have been proposed. However, different evaluation methodologies make direct comparison difficult. We address this shortcoming with a thorough and fair comparison of thirteen state-of-the-art superpixel algorithms.
openaire +1 more source
Image Segmentation via Clustering Superpixels
, 2012 This paper presents a method for image segmentation by clustering superpixels based on histogram dissimilarity. A superpixel is a tiny image fragment which contains the edge or boundary information of sub-regions in the image. Each sub-region consists of
유지성, 김성대, 황성수
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Double-Branch Multilevel Skip Sparse Graph Attention Network for Hyperspectral Image Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingGraph neural networks (GNNs) offer a potent framework for learning and representing data with graph structures. In the context of hyperspectral images (HSIs) classification tasks, GNNs have been successfully employed. Among the diverse variations of GNNs,
Qingyan Wang +4 more
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Class-specified segmentation with multi-scale superpixels
, 2013 Conference Name:11th Asian Conference on Computer Vision, ACCV 2012. Conference Address: Daejeon, Korea, Republic of. Time:November 5, 2012 - November 6, 2012.This paper proposes a class-specified segmentation method, which can not only segment ...
Wu, Yang +8 more
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V.: SEEDS: Superpixels extracted via energy-driven sampling
, 2020 . Superpixel algorithms aim to over-segment the image by grouping pixels that belong to the same object. Many state-of-the-art superpixel algorithms rely on minimizing objective functions to enforce color homogeneity.
Michael Van Den Bergh +4 more
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SuperPatchMatch : Un algorithme de correspondances robustes de patchs de superpixels
, 2018 Les superpixels sont devenus très populaires dans de nombreuses applications de vision par ordinateur. Néanmoins, ils restent sous-exploités du fait de l'irrégularité des décompositions qui diffèrent selon les images. Dans ce travail, nous introduisons d'
GIRAUD, Rémi +4 more
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GeomaticsRice field mapping is essential for effective agricultural and water resource management due to high land pressure. This study aims to map paddy rice by combining segmentation techniques and phenological metrics derived from optical time series.
Fama Mbengue +5 more
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